Single-cell transcriptomic analysis of gingivo-buccal oral cancer reveals two dominant cellular programs.

Sillarine Kurkalang, Sumitava Roy, Arunima Acharya, Paramita Mazumder, Somnath Mazumder,Subrata Patra,Shekhar Ghosh,Sumanta Sarkar, Sudip Kundu,Nidhan Kumar Biswas,Sandip Ghose,Partha P Majumder,Arindam Maitra

Cancer science(2023)

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摘要
Oral squamous cell carcinoma of the gingivo-buccal region (OSCC-GB) is the most common cancer among men in India, and is associated with poor prognosis and frequent recurrence. Cellular heterogeneity in OSCC-GB was investigated by single-cell RNA sequencing of tumors derived from the oral cavity of 12 OSCC-GB patients, 3 of whom had concomitant presence of a precancerous lesion (oral submucous fibrosis [OSMF]). Unique malignant cell types, features, and phenotypic shifts in the stromal cell population were identified in oral tumors with associated submucous fibrosis. Expression levels of FOS, ATP1A, and DUSP1 provided robust discrimination between tumors with or without the concomitant presence of OSMF. Malignant cell populations shared between tumors with and without OSMF were enriched with the expression of partial epithelial-mesenchymal transition (pEMT) or fetal cell type signatures indicative of two dominant cellular programs in OSCC-GB-pEMT and fetal cellular reprogramming. Malignant cells exhibiting fetal cellular and pEMT programs were enriched with the expression of immune-related pathway genes known to be involved in antitumor immune response. In the tumor microenvironment, higher infiltration of immune cells than the stromal cells was observed. The T cell population was large in tumors and diverse subtypes of T cells with varying levels of infiltration were found. We also detected double-negative PLCG2+ T cells and cells with intermediate M1-M2 macrophage polarization. Our findings shed light on unique aspects of cellular heterogeneity and cell states in OSCC-GB.
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关键词
cellular diversity,fetal cell-type signature,partial epithelial-mesenchymal transition,single-cell RNA sequencing,tumor ecosystem
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